Rényi Entropy Power and Normal Transport

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A framework for deriving Rényi entropy-power inequalities (REPIs) is presented that uses linearization and an inequality of Dembo, Cover, and Thomas. Simple arguments are given to recover the previously known Rényi EPIs and derive new ones, by unifying a multiplicative form with constant c and a modification with exponent α of previous works. An information-theoretic proof of the Dembo-Cover-Thomas inequality - equivalent to Young's convolutional inequality with optimal constants - is provided, based on properties of Rényi conditional and relative entropies and using transportation arguments from Gaussian densities. For log-concave densities, a transportation proof of a sharp varentropy bound is presented.This work was partially presented at the 2019Information Theory and Applications Workshop, San Diego, CA.

Original languageEnglish
Title of host publicationProceedings of 2020 International Symposium on Information Theory and its Applications, ISITA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9784885523304
DOIs
Publication statusPublished - 24 Oct 2020
Event16th International Symposium on Information Theory and its Applications, ISITA 2020 - Virtual, Kapolei, United States
Duration: 24 Oct 202027 Oct 2020

Publication series

NameProceedings of 2020 International Symposium on Information Theory and its Applications, ISITA 2020

Conference

Conference16th International Symposium on Information Theory and its Applications, ISITA 2020
Country/TerritoryUnited States
CityVirtual, Kapolei
Period24/10/2027/10/20

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